Magnetometer Calibration Using Time-Selected Measurements
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Solution Overview
Problem
Magnetometers in mobile devices require frequent recalibration to compensate for hard and soft iron biases, which is inconvenient for users and can be inaccurate if not performed correctly, especially when recalibrating frequently.
Innovation Solution
A method for magnetometer calibration using selected measurements over time, where multiple sets of magnetic field measurements are obtained and error values are calculated to identify hard iron bias values, allowing for calibration without the need for precise user-movement patterns, by constraining or weighting measurements based on conditions such as time, distance, and magnetic environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional magnetometer calibration methods are used, then calibration accuracy can be maintained, but user convenience deteriorates due to frequent recalibration requirements and complex movement patterns
Solution Approach 1:
The system performs self-calibration by automatically selecting appropriate measurements from accumulated data based on predefined criteria, eliminating the need for user intervention in the calibration process while maintaining accuracy through algorithmic selection of valid calibration moments
Solution Approach 2:
The system continuously accumulates magnetic field measurements in advance and pre-processes them to identify calibration opportunities, so that when calibration is needed, valid measurement data is already available without requiring user action at that moment
2Measurement precision
If frequent recalibration is performed to maintain accuracy, then measurement precision improves, but device complexity increases due to processing requirements
Solution Approach 1:
The system extracts only the essential calibration information from accumulated measurements by applying selection criteria to identify measurements taken during valid calibration conditions, processing only the necessary subset of data rather than all accumulated measurements
Solution Approach 2:
The system accumulates more measurements than strictly necessary for calibration, allowing selective processing of a subset that meets calibration criteria, which simplifies the processing of individual calibration events while ensuring data quality
3Measurement precision
If precise calibration patterns are required, then calibration accuracy improves, but ease of operation deteriorates due to user burden
Solution Approach 1:
The system automatically determines when calibration conditions are met by monitoring measurement data against predefined criteria, eliminating the need for users to follow specific movement patterns or initiate calibration procedures manually
Solution Approach 2:
The system continuously monitors magnetic field measurements and provides feedback on calibration quality, automatically adjusting the selection of calibration measurements based on whether they meet accuracy criteria, ensuring precision without user intervention
Data Source
AI summary
Certain aspects of the present disclosure generally relate to magnetometer calibration. In some aspects, a device may obtain multiple sets of magnetic field measurements corresponding to multiple local magnetic field strengths, wherein each set of magnetic field measurements is measured in association with an unknown local magnetic field strength. The device may calculate multiple error values using the multiple sets of magnetic field measurements, estimated values of the multiple local magnetic field strengths, and estimated hard iron bias values. The device may identify a set of hard iron bias values for magnetometer calibration based at least in part on comparing the multiple error values. The device may calibrate a magnetometer using the identified set of hard iron bias values.